negotiation_agent

negotiation_agent

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negotiation_agent is a Python library that leverages large language models to automate negotiation dialogues. It enables users to define negotiation domains with items and utility functions, configure agent strategies, and simulate end-to-end bargaining processes. The framework offers built-in protocols for offers and counteroffers, detailed evaluation metrics for deal quality, and extensible components for custom agent behaviors, making it ideal for research and prototyping.
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May 13 2025
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What is negotiation_agent?

negotiation_agent provides a modular toolkit for building autonomous negotiation bots powered by GPT-like models. Developers can specify negotiation scenarios by defining items, preferences, and utility functions to model agent objectives. The framework includes pre-defined agent templates and allows integration of custom strategies, enabling offer generation, counteroffer evaluation, acceptance decisions, and deal closure. It manages dialogue flows using standardized protocols, supports batch simulations for tournament-style experiments, and calculates performance metrics such as agreement rate, utility gains, and fairness scores. The open architecture facilitates swapping underlying LLM backends and extending agent logic through plugins. With negotiation_agent, teams can quickly prototype and evaluate automated bargaining solutions in e-commerce, research, and educational settings.

Who will use negotiation_agent?

  • AI researchers in multi-agent systems and game theory
  • Developers prototyping negotiation bots
  • E-commerce platforms seeking automated bargaining features
  • Students learning negotiation strategies and computational economics

How to use the negotiation_agent?

  • Step1: Install the library using pip: pip install git+https://github.com/markvasin/negotiation_agent.git
  • Step2: Define a negotiation domain by specifying items and utility functions
  • Step3: Instantiate agents with chosen LLM backends and strategies
  • Step4: Run negotiations via run_negotiation(agent1, agent2, domain)
  • Step5: Gather and analyze negotiation metrics using provided evaluation tools
  • Step6: Customize agent behaviors by extending template classes or plugins

Platform

  • Linux
  • Mac
  • Windows

negotiation_agent's Core Features & Benefits

The Core Features

  • Domain modeling with items and utility functions
  • LLM-based agent templates for negotiation
  • Standardized offer and counteroffer protocols
  • Batch simulation for tournaments and experiments
  • Performance metrics: agreement rate, utility, fairness
  • Extensible architecture for custom strategies and plugins

The Benefits

  • Rapid prototyping of negotiation scenarios
  • Seamless integration with GPT-like models
  • Reproducible evaluation and benchmarking
  • Highly customizable agent behaviors
  • Open-source MIT License

negotiation_agent's Main Use Cases & Applications

  • Automated e-commerce price negotiation
  • Research on bargaining strategies and outcomes
  • Customer service chatbots handling offers
  • Educational simulations in economics courses

FAQs of negotiation_agent

negotiation_agent Company Information

negotiation_agent Reviews

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negotiation_agent's Main Competitors and alternatives?

ParlAI negotiation tasks
Open Negotiator frameworks
DealMaker by Microsoft
TacNegotiator

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